Bibliographic description:
Matsiuk, Markiian. Recognition of continious arm movement based on electromyography data: Bachelor Thesis: manuscript / Markiian Matsiuk; Supervisor: Oleh Farenyuk; Ukrainian Catholic University, Department of Computer Sciences. – Lviv: 2021. – 50 p.: ill.
Abstract:
Currently, neural-computer interfaces require expensive hardware, which is not available
for most researchers, while EMG sensors are cheap, affordable, and quite robust.
That makes them an attractive option for a wide class of devices, like prostheses,
game devices, or exoskeletons. So reliable and accurate methods of EMG data
recognition and interpretation are required. While most of the popular methods of
EMG data analysis include only distinct gesture recognition, in this thesis we try
to implement the system, which recognizes continuous motion on the example of
arm movement and end effector (palm) pose estimation. This thesis goal is to prove
that this kind of estimation is possible by creating a system that will estimate arm
position in 3d space.
